fix: use json_repair for robust LLM response parsing

nanobot/agent/loop.py

@@ -3,6 +3,7 @@
 import asyncio
 from contextlib import AsyncExitStack
 import json
+import json_repair
 from pathlib import Path
 from typing import Any
 
@@ -420,9 +421,15 @@ Respond with ONLY valid JSON, no markdown fences."""
                 model=self.model,
             )
             text = (response.content or "").strip()
+            if not text:
+                logger.warning("Memory consolidation: LLM returned empty response, skipping")
+                return
             if text.startswith("```"):
                 text = text.split("\n", 1)[-1].rsplit("```", 1)[0].strip()
-            result = json.loads(text)
+            result = json_repair.loads(text)
+            if not isinstance(result, dict):
+                logger.warning(f"Memory consolidation: unexpected response type, skipping. Response: {text[:200]}")
+                return
 
             if entry := result.get("history_entry"):
                 memory.append_history(entry)

nanobot/providers/litellm_provider.py

@@ -1,6 +1,7 @@
 """LiteLLM provider implementation for multi-provider support."""
 
 import json
+import json_repair
 import os
 from typing import Any
 
@@ -173,10 +174,7 @@ class LiteLLMProvider(LLMProvider):
                 # Parse arguments from JSON string if needed
                 args = tc.function.arguments
                 if isinstance(args, str):
-                    try:
-                        args = json.loads(args)
-                    except json.JSONDecodeError:
-                        args = {"raw": args}
+                    args = json_repair.loads(args)
                 
                 tool_calls.append(ToolCallRequest(
                     id=tc.id,